AI Data Architect

Role & responsibilities:

MGT is a US-based management consulting firm serving public sector and education agencies, alongside clients in technology, finance, and advisory. With several decades of experience and significant recent growth, MGT has built a dedicated AI Operating Group (AI OG) focused on designing, building, and deploying AI-powered solutions across the firm and its clients. The India team is a fully integrated global delivery function, working in close collaboration with US-based consultants and product leads.

• Design and implement scalable data architectures for AI, machine learning, and analytics workloads.
• Lead architecture decisions for complex AI and data initiatives and establish best practices for data engineering, governance, and

platform design.

• Build and maintain ETL/ELT pipelines for structured and unstructured data sources.
• Develop and manage data lakes, data warehouses, and feature stores to support model training and inference.
• Ensure data quality, governance, lineage, and observability across AI data ecosystems.
• Collaborate with AI engineers, data scientists, and solution architects to define data requirements and optimize performance.
• Design secure and compliant data solutions aligned with public sector standards and regulations.
• Implement cloud-native data platforms and modern data engineering frameworks.
• Support the development of vector databases and retrieval pipelines for generative AI applications.
• Document architectures, data models, metadata, and technical standards.
• Evaluate emerging technologies and recommend improvements to existing data platforms.

• 7+ years of experience in Data Architecture, Data Engineering, or related fields.
• Strong experience designing and building scalable data pipelines and platforms for AI/ML use cases.
• Advanced proficiency in Python and SQL.
• Hands-on experience with modern cloud platforms (AWS, Azure, or GCP).
• Hands-on experience with modern data stack technologies such as Spark, Airflow, dbt, Snowflake, Databricks, Kafka, and Terraform.
• Experience with data warehousing, data lakes, distributed processing, and large-scale data systems.
• Strong understanding of data modeling, governance, security, and quality management best practices.
• Excellent written and verbal English communication skills.
• Ability to work independently in a fully remote, U.S.
  
  -aligned environment.
• Strong problem-solving skills and ability to translate business requirements into technical solutions.

• Experience building vector databases such as Pinecone or Weaviate and Retrieval-Augmented Generation (RAG) pipelines.
• Experience supporting government, education, or other regulated public sector organizations.
• Familiarity with compliance frameworks such as FedRAMP, NIST, or data privacy regulations.
• Knowledge of event-driven architectures and real-time data streaming platforms.
• Experience working in consulting or client-facing environments.
• Cloud or data certifications (AWS, Azure, GCP, Databricks, Snowflake, or equivalent)